The work [1]} proposed an RNN based HSIC framework with a novel activation function (parametric rectified tanh) and GRU, which utilizes the sequential property of HSI to determine the class labels. In [2]} a local spatial sequential (LSS) method based RNN framework was introduced which first extracts low-level features from HSI by using Gabor filter and differential morphological profiles [3]} and then fuse these features together to obtain LSS features from the proposed method, these LSS features are further passed to an RNN model to extract high-level features, while a softmax layer is used for final classification.
